Correlations and path analysis among agronomic and technological traits of upland cotton

Abstract

ABSTRACT. To date, path analysis has been used with the aim of breeding different cultures. However, for cotton, there have been few studies using this analysis, and all of these have used fiber productivity as the primary dependent variable. Therefore, the aim of the present study was to identify agronomic and technological properties that can be used as criteria for direct and indirect phenotypes in selecting cotton genotypes with better fibers. We evaluated 16 upland cotton genotypes in eight trials conducted during the harvest 2008/2009 in the State of Mato Grosso, using a randomized block design with four replicates. The evaluated traits were: plant height, average boll weight, percentage of fiber, cotton seed yield, fiber length, uniformity of fiber, short fiber index, fiber strength, elongation, maturity of the fibers, micronaire, reflectance, and the degree of yellowing. Phenotypic correlations between the traits and cotton fiber yield (main dependent variable) 2 F.J.C. Farias et al. Genetics and Molecular Research 15 (3): gmr.15038239 were unfolded in direct and indirect effects through path analysis. Fiber strength, uniformity of fiber, and reflectance were found to influence fiber length, and therefore, these traits are recommended for both direct and indirect selection of cotton genotypes.

Adaptability and Stability of Cotton Genotypes Regarding Fiber Yield and Quality Traits

“…Significant G´E interaction for FY in Mato Grosso had been previously verified by Souza et al (2006), Suinaga et al (2006), andFarias et al (2016). Similar results were observed by other authors in studies on cotton agronomic and fiber quality traits (Campbell and Jones, 2005;Baxevanos et al, 2008, Ng et al, 2013, Carvalho et al, 2015, Farias et al, 2016.…”

“…In cotton cultivar evaluation trials in Spain, Baxevanos et al (2008) adopted a more complete selection index where selection index (SI) = 0.6(yield) + 0.1(lint percentage + FL + FS) + 0.05 (uniformity + elongation), in which micronaire remained ignored. Besides, lint percentage is highly correlated with lint yield (Farias et al, 2016), so it can be argued that there was some redundancy in the formula. In the national cotton registration standards currently implemented in China, the selection index can be presented as a linear combination (Xu et al, 2017): SI = −0.17(FL) + 0.30(FS) − 0.19(micronaire) + 0.93 (yield) + 0.14(lint percentage).…”

Genetic diversity among cotton cultivars in two environments in the State of Mato Grosso

“…In the world, Brazil is the fifth larger producer of seed cotton, with 4.4 million tons in the harvest of 2013/2014 (CONAB -Companhia Nacional de Abastecimento, 2015). The State of Mato Grosso is the largest national producer primarily in the municipalities of Primavera do Leste, Lucas do Rio Verde, and Sapezal (CONABCompanhia Nacional de Abastecimento, 2015;Farias et al, 2016).…”

Early selection of sugarcane using path analysis

“…The technique, introduced by Wright (1921Wright ( , 1923 and described in detail by Li (1956Li ( , 1975, identifies miscorrelations between two traits that may not necessarily be related by direct cause-andeffect, because of the influence of a third trait. Path analysis has been widely used by plant breeders in a variety of crops, e.g., soybean (Peter et al, 2014), corn (Faria et al, 2015), common bean (Cabral et al, 2011), green bean (Araujo et al, 2012), cowpea (Moura et al, 2012;Santos et al, 2014), rice (Marchezan et al, 2005), wheat (Kavalco et al, 2014), cotton (Hoogerheide et al, 2007;Farias et al, 2016), sweet sorghum (Lombardi et al, 2015), and sugarcane (Saccharum officinarum) (Kang et al, 1983;Reddy and Reddy, 1986;Sukhchain and Sain, 1997;Ferreira et al, 2007;Silva et al, 2009;Souza et al, 2011;Esposito et al, 2012). However, studies of this nature are still necessary, because different population structures, environments, and management strategies should be considered.…”